Recovery Process Optimization Using Survival Regression

FFA Working Paper 4/2020, University of Economics, Prague.

25 Pages Posted: 30 Sep 2020

See all articles by Jiri Witzany

Jiri Witzany

University of Economics in Prague

Anastasiia Kozina

affiliation not provided to SSRN

Date Written: August 14, 2020

Abstract

The goal of this paper is to propose, empirically test and compare different logistic and survival analysis techniques in order to optimize the debt collection process. This process uses various actions, such as phone calls, mails, visits, or legal steps to recover past due loans. We focus on the soft collection part, where the question is whether and when to call a past-due debtor with regard to the expected financial return of such an action. We propose using the survival analysis technique, in which the phone call can be compared to a medical treatment, and repayment to the recovery of a patient. We show on a real banking dataset that, unlike ordinary logistic regression, this model provides the expected results and can be efficiently used to optimize the soft collection process.

Keywords: credit risk modelling, survival analysis, scoring, receivables, debt recovery, collection, retail banking, credit risk

JEL Classification: G21, G28, C14

Suggested Citation

Witzany, Jiri and Kozina, Anastasiia, Recovery Process Optimization Using Survival Regression (August 14, 2020). FFA Working Paper 4/2020, University of Economics, Prague., Available at SSRN: https://ssrn.com/abstract=3673879 or http://dx.doi.org/10.2139/ssrn.3673879

Jiri Witzany (Contact Author)

University of Economics in Prague ( email )

Winston Churchilla Sq. 4
Prague 3, 130 67
Czech Republic

Anastasiia Kozina

affiliation not provided to SSRN

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